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粤港澳大湾区科技基础设施的空间集聚与区域发展效应
引用本文:王洋,张虹鸥,岳晓丽.粤港澳大湾区科技基础设施的空间集聚与区域发展效应[J].地理科学进展,2022,41(9):1702-1715.
作者姓名:王洋  张虹鸥  岳晓丽
作者单位:1.云南师范大学地理学部,昆明 650500
2.广东省科学院广州地理研究所,广东省遥感与地理信息系统应用重点实验室/广东省地理空间信息技术与应用公共实验室
3.粤港澳大湾区战略研究院,广州 510070
4.广东工业大学建筑与城市规划学院,广州 510090
基金项目:国家自然科学基金重点项目(42130712);国家自然科学基金项目(41871150);国家自然科学基金项目(42101182);粤港澳大湾区战略研究院建设专项(2021GDASYL-20210401001)
摘    要:为探究科技基础设施的空间分布特征和区域发展效应,论文以粤港澳大湾区688个科技基础设施为研究对象,以56个县区为基本研究单元,采用平均最近邻距离法分析粤港澳大湾区科技基础设施的空间集聚性与空间差异格局。基于地理探测器从经济水平、居住收入、住房价格、人口学历结构4个方面分析粤港澳大湾区科技基础设施的区域发展效应。结果表明:① 粤港澳大湾区科技基础设施呈现高度的空间集聚性分布,主要集中在广州核心区、深圳南山区和香港南部地区,在县区尺度上具有显著的空间差异和空间极化现象;② 粤港澳大湾区科技基础设施分布对人口学历结构、经济水平、住房价格的空间格局具有显著的正向影响,显示出区域发展效应;③ 不同性质科技基础设施的区域发展效应有所差别,基础研究类科技基础设施对人口学历结构的影响强度最高,应用类科技基础设施对经济水平的影响最为明显。该研究可为粤港澳大湾区创新地理的学术研究提供案例补充,也为粤港澳大湾区科技基础设施的合理布局和优化配置提供决策支撑,具有学术意义和现实价值。

关 键 词:科技基础设施  创新地理  创新的区域效应  粤港澳大湾区  
收稿时间:2022-01-20
修稿时间:2022-06-22

Spatial agglomeration and regional development effects of science and technology infrastructures in the Guangdong-Hong Kong-Macao Greater Bay Area
WANG Yang,ZHANG Hong'ou,YUE Xiaoli.Spatial agglomeration and regional development effects of science and technology infrastructures in the Guangdong-Hong Kong-Macao Greater Bay Area[J].Progress in Geography,2022,41(9):1702-1715.
Authors:WANG Yang  ZHANG Hong'ou  YUE Xiaoli
Abstract:This study explored the spatial distribution characteristics and regional development effects of science and technology infrastructure in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Taking 688 science and technology infrastructures as the research objects and 56 counties as the basic spatial units, it analyzed the spatial agglomeration and spatial differentiation patterns of science and technology infrastructures in 2020 in the GBA using the average nearest neighbor analysis method. This study combined the Geodetector output to illustrate the regional development effects of science and technology infrastructures in the GBA from four aspects: economic development level, residents' income, housing price, and population educational structure. The evaluation indicators for the four aspects are GDP per capita, per capita disposable income of urban residents, average housing price, and the number of university-educated persons per 100000 people respectively. The results indicate that: 1) The science and technology infrastructures show a remarkable spatial clustering distribution, mainly concentrated in the core area of Guangzhou, Nanshan District of Shenzhen, and the southern area of Hong Kong, with significant spatial differentiation and polarization at the county scale. 2) The science and technology infrastructure distribution in the GBA has a significant positive impact on the spatial patterns of population educational structure, economic development level, and housing price, showing a regional development effect. 3) The regional development effects of different science and technology infrastructures vary. The basic research science and technology infrastructures have the highest impact on the educational structure of the population, and the applied science and technology infrastructures have the most obvious impact on the economic development level. This study provides an additional case for academic research on the innovation geography of the GBA and decision support for the optimal layout and allocation of science and technology infrastructures in the GBA, which has both scientific and practical values.
Keywords:science and technology infrastructure  innovation geography  regional effects of innovation  Guangdong-Hong Kong-Macao Greater Bay Area  
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